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AI & Machine Learning · Intermediate

Agent Loop

The repeated cycle in which an agent calls the model, executes requested tools and feeds results back until the task completes.

Definition

Each iteration sends the conversation and tool results to the model; if the model requests a tool, the application runs it and appends the result. The loop ends when the model returns a final answer or a limit is hit. ReAct (reason + act) is a well-known formulation.

Exam tip

Always set iteration, token and cost limits on agent loops.

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